000			01929nam a2200265 4500
001			394577
090			_a394577
100			_a20170525d2017 y0pory50 ba
101			_aeng
200			_aA framework for performing forensic and investigatory speaker comparisons using automated methods _bRecurso eletrónico _fDavid Brian Marks
210			_aDenver _c[s.n.] _d2017
215			_a1 CD-ROM _d12 cm
300			_aTese de Mestrado apresentada à Universidade do Colorado, tendo como orientadora Catalin Grigoras. Ficheiro de 2,99 MB em formato PDF (174 p.).
330			_aI. INTRODUCTION. Terminology. Challenges of Voice Forensics. Scope. II. BACKGROUND. Scientific Foundations. The Scientific Method. Bias Effects. Legal Foundations. Rules of Evidence. Federal Case Law. State Case Law. Factors in Speaker Recognition. The Nature of the Human Voice. Speaker Recognition Systems. Bias Effects. Standards. Historical Baggage. III. COMPARISON FRAMEWORK. Case Assessment. Forensic Request. Administrative Assessment. Technical Assessment. Decision to Proceed with Analysis. Analysis and Processing. Data Preparation. Data Enhancement. Selection of the Relevant Population. System Performance and Calibration. Combining Results from Multiple Methods or Systems. Conclusions. Interpreting Results. Communicating Results. Case Studies. Case Study 1. Case Study 2. Case Study 3. SUMMARY AND CONCLUSIONS. Challenges in the Relevant Population. Fusion for Multiple Algorithms. Verbal Scale Standards for Reporting Results. Data and Standards for Validation. REFERENCES.
606			_aIDENTIFICAÇÃO DA VOZ _9345486
606			_aEXAME À VOZ _9346274
606			_aREGISTO VOCAL _9343486
606			_aMETODOLOGIAS _9341295
606			_aSOFTWARE _9235148
606			_aTESE _9334284
606			_aESTADOS UNIDOS _9334103
700			_aMARKS _bDavid Brian _9358463
955			_xOferta